The Penn TURBO (Transforming and Unifying Research with Biomedical Ontologies) project aims to accelerate finding and connecting key information from clinical records for research through semantic associations to the processes that generated the clinical data. Major challenges to using clinical data for research are integrating data from different sources which may contain multiple references to the same entity (e.g., person, health care encounter) and incomplete or conflicting information (e.g., gender, BMI). There is also the need to track the provenance of information used when making decisions on what is the actual phenotype of a person. We take a realism-based ontology approach to address these problems through transformation and instantiation of clinical data with an OBO-Foundry based application ontology in a semantic graph database. We have developed an application stack and used it on an 11,237 whole exome sequencing patient cohort capturing key demographics, diagnosis codes, and prescribed medications. The anticipated payoff is to be able to make use of inferencing provided by the semantics to classify and search for instances of people and specimens with desired characteristics.